At a Glance
- Tasks: Develop advanced models and analytics to optimise revenue and manage risk in finance.
- Company: Join a leading financial services firm with a focus on innovation and collaboration.
- Benefits: Competitive salary, professional development, and unique growth opportunities.
- Other info: Collaborative environment with opportunities to mentor and grow your career.
- Why this job: Make a real impact by solving complex business challenges with cutting-edge technology.
- Qualifications: Advanced degree in a quantitative field and strong experience in modelling and analytics.
The predicted salary is between 90000 - 110000 £ per year.
The Prime Finance Quantitative Trading and Research (QTR) team in London develops and maintains advanced mathematical models, innovative methodologies, and robust infrastructure to support and grow the Prime Financial Services business.
Our mission is to optimize decision-making, automate processes, and manage and hedge risk.
Prime Financial Services provides financing and securities lending to institutional investors, optimizes the bank's inventory and balance sheet, and delivers strategic solutions to clients.
The QTR team partners closely with trading, technology, and risk teams to deliver impactful tools and analytics.
The team specializes in building models that leverage Machine Learning, Statistics, and Operations Research to solve complex business challenges.
As a Vice President in QTR Prime Finance, you will collaborate with senior stakeholders to design and implement those models and help drive business revenue, enhance risk management, and automate workflows.
Typical projects include predicting changes in borrow rates or forecasting market demand, unraveling patterns and causality in the data, researching alpha signals and optimizing pricing and inventory allocation to maximize our revenue and profits.
As Vice President in the team you will be involved in regular collaboration with the trading desk.
In addition to strong technical expertise, excellent communication skills are essential for effectively engaging with stakeholders and translating complex quantitative concepts into actionable business solutions.
Experience in Prime Financeis preferred but not required.
We provide on-job training, and through the diversity of the businesses it supports and the variety of functions that it is responsible for, the QTR group provides unique growth opportunities for you to develop your abilities and your career.
Job responsibilities
- Develop and implement mathematical, statistical, and machine learning models to optimize revenue and profitability for stock borrow-loan, cash, and synthetic financing books, as well as predictive analytics to forecast borrow rates, product demand, and other key business drivers.
- Apply operations research and optimization techniques to automate and enhance traders' decision-making and inventory management.
- Analyse market data to uncover patterns, causality and inform business strategy.
- Research and develop alpha signals and automated hedging strategies, both to assist in the systematic trading efforts of the firm and to contribute to the suite of commercialised datasets of the business
- Collaborate with trading, technology, and risk teams to deliver quantitative tools and solutions.
- Build and maintain robust infrastructure for model deployment and analytics delivery.
- Ensure models and analytics meet rigorous control and risk management standards.
- Continuously improve existing models and methodologies in response to evolving business needs.
- Communicate complex quantitative concepts to senior stakeholders and non-technical audiences.
- Mentor junior team members and contribute to a collaborative team environment.
- Document models, methodologies, and processes for transparency and knowledge sharing.
- Required Qualifications, Capabilities and Skills
- Advanced degree (Masters or Ph D) in Statistics, AI/ML, Computer Science, Operations Research, or related quantitative field.
- Significant experience in quantitative modelling, analytics, or related roles.
- Strong background in AI, machine learning, operations research, or revenue/yield management.
- Proficiency in Python for data analysis, modelling, and software development.
- Deep understanding of statistics, AI, and optimization techniques.
- Demonstrated ability to solve complex quantitative problems and deliver business impact.
- Excellent communication and presentation skills, especially with senior stakeholders.
- Ability to work collaboratively in cross-functional teams.
- Strong organizational skills and attention to detail.
- Experience with large-scale data analysis and visualization tools.
- Preferred Qualifications Capabilities and Skills
- Experience with systematic trading and alpha signal research
- Experience in Prime Finance, securities lending, or inventory management.
- Familiarity with revenue and yield management strategies.
- Hands-on experience with machine learning frameworks (e. g., scikit-learn, Tensor Flow, Py Torch).
- Knowledge of optimization libraries and techniques (e. g., Gurobi, CPLEX, linear/nonlinear programming).
- Track record of publishing research or presenting at industry conferences.
- Experience mentoring or leading junior researchers.
- #J-18808-Ljbffr
Quantitative Trading & Research – Prime Finance Quantitative Research – Vice President employer: JPMorgan Chase & Co.
JPMorgan Chase & Co. is an exceptional employer, offering a dynamic work environment in the heart of London’s International Private Bank. With a strong emphasis on professional development, employees benefit from comprehensive training programs and opportunities for career advancement, all while enjoying a collaborative culture that values teamwork and innovation. The role of Executive Assistant not only provides a chance to work closely with senior leaders but also allows for meaningful contributions to the success of the team in a prestigious financial institution.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Trading & Research – Prime Finance Quantitative Research – Vice President
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like JPMorgan Chase & Co.!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Quantitative Trading & Research – Prime Finance Quantitative Research – Vice President at JPMorgan Chase & Co..
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like JPMorgan Chase & Co..
✨Apply Directly through Our Website
When you find a suitable opening like Quantitative Trading & Research – Prime Finance Quantitative Research – Vice President at JPMorgan Chase & Co., make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Quantitative Trading & Research – Prime Finance Quantitative Research – Vice President
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at JPMorgan Chase & Co., your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at JPMorgan Chase & Co.. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at JPMorgan Chase & Co.
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at JPMorgan Chase & Co.!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
